FlexiLoans - Senior Data Scientist

Senior Data Scientist

Who we are:

FlexiLoans is a technology based Digital financing platform started with an endeavour to solve the problems that small businesses face in accessing Quick, Flexible and Adequate funds for growing their Businesses. Our vision is to give "Financial access at a click". Our talent pool has rockstars from diverse backgrounds - ex- Founders, investment bankers, e-commerce and payments with the passion to make a difference to the lives of 70 mn+ MSME businesses in India.

FlexiLoans.com is a pioneer in the ecosystem-based digital lending for small businesses in India. Till date, we have disbursed over 45,000+ loans worth over Rs. 1600 Crs+ to small sized businesses across 1,600+ cities without having a single branch! We are the leaders in using technology and risk models that focus on alternate / surrogate methods for scoring customers. Our origination is 100% digital with over 100 embedded partnerships like Amazon, Flipkart, Nykaa, Paisabazaar, etc. for providing credit access to MSME businesses.

Founded by CA/ISB alumni, FlexiLoans is funded by marquee bankers such as Sanjay Nayar (Chairman, KKR and Ex-CEO, Citibank South Asia), Gunit Chaddha (Ex-CEO, Deutsche Bank, Asia Pacific), Anil Jaggia (Ex-CIO, HDFC Bank), Vikram Sud (Ex-COO, Kotak Mahindra Bank), Narayan Seshadri (Ex-Managing Partner, KPMG), Gopal Srinivasan (Chairman, TVS Capital) and Siddharth Parekh (Co-Founder, Paragon Partners) to name a few.

VALUES OF FLEXILOANS - COLLABORATION | AGILITY | INNOVATION | RESPECT | OWNERSHIP

Why join us?

A certified Great Place to work and Young team with a diverse mix of Gender, Background, Fun@work, and Responsibility with authority are a few things that you can expect while working with the passionate team at FlexiLoans!

Join us!

FlexiLoans is looking at candidates to join us as we continue our amazing growth trajectory. Sounds like you? Read more on what are we looking for in the role

Duties and responsibilities:

- Lead a team of data scientist in designing, developing and implementation of advanced machine learning models in the lending domain

- Perform data analytics and keen to learn/explore new techniques,

- Perform exploratory analysis using structured/unstructured data,

- Oversee and build statistical models/scorecards within specified timelines,

- Co-ordinate with various internal teams Credit, Product, Business etc,

- Bring fresh ideas to the table and keen observers of trends on analytics and financial services industry,

- Work on a variety of projects of different nature Credit Risk, Business, Product, Data Management etc,

- Utilize cloud services, particularly AWS, for scalable and efficient model deployment.

- Apply supervised and unsupervised learning algorithms for predictive modeling and data analysis.

- Develop and maintain Python-based machine learning solutions for various business needs.

- Ensure model explainability and interpretability using AI techniques.

- Utilize SQL for data extraction, manipulation, and analysis.

- Utilize Power BI or any visualization tool for data visualization and reporting.

- Experience or exposure to text analytics for extracting insights from unstructured data.

- Collaborate with cross-functional teams to create and deploy ML models in production.

- Knowledge of ML production practices (MLOPS) is desirable.

- Ability to create APIs for model integration (desired but not mandatory).

Requirements and Skill Sets:

- Strong domain knowledge of retail lending business - Underwriting, Product & Pricing, Campaigns, Risk Management & Collections

- Worked across any of the below domain

- Credit Risk Scorecards

- Collection Scorecards

- Risk Policy defining and simulation

- Statistical Models across customer Life - cycle

- Customer Lifetime Value

- Risk based Pricing Analytics

Technical Skills:

- Successfully develop and deploy advanced analytics solutions including statistical modelling, machine learning techniques such as logistic regression, Random Forest, XGBoost, Decision Tree, Clustering techniques, PCA,

- Collaborative Filtering, Neural Networks, Time-series etc

- Strong programming skills (at least one of R/Python), SQL, Excel & MS office skills etc

- 4-5 years of hands-on experience in machine learning.

- Strong experience in the lending domain with a minimum of 2 years.

- Proficiency in cloud services, particularly AWS.

- Expertise in supervised and unsupervised learning algorithms.

- Strong proficiency in Python programming for data analysis and model development.

- Experience in model explain-ability techniques in AI.

- Strong SQL skills for data handling and analysis.

- Proficiency in Power BI or any visualization tool for data visualization.

- Exposure to text analytics is advantageous.

- Knowledge of ML production practices (MLOPS) is desirable.

- Bash scripting skills would be an added advantage.

Other Requirements:

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration skills.

- Ability to work in a dynamic and fast-paced environment

Qualification and Experience:

- MBA/BE/ Masters Statistics/ Mathematics/ Master's degree in Statistics, Mathematics, Engineering, or related field/ Specialization or degree in Artificial Intelligence/Machine Learning, with work experience up 4+ years in Analytics, Model building & Data Management. Worked with analytics consulting into financial services, Indian Bank s/NBFCs in-house analytics units or Fintech/analytics start-ups is must.

- 2+ years of team handling/leading experience